7 citations · 16 across the 7 of their papers we have counts for
7 papers
Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs
Yanqi Bao, Yuxin Li, Jing Huo +4
Neural Radiance Fields from Sparse input} (NeRF-S) have shown great potential in synthesizing novel views with a limited number of observed viewpoints. However, due to the inherent…
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo +3
Generalizing Neural Radiance Fields (NeRF) to new scenes is a significant challenge that existing approaches struggle to address without extensive modifications to vanilla NeRF fra…
Automated Search-Space Generation Neural Architecture Search
Tianyi Chen, Luming Liang, Tianyu Ding +1
To search an optimal sub-network within a general deep neural network (DNN), existing neural architecture search (NAS) methods typically rely on handcrafting a search space beforeh…
OTOV2: Automatic, Generic, User-Friendly
Tianyi Chen, Luming Liang, Tianyu Ding +2
The existing model compression methods via structured pruning typically require complicated multi-stage procedures. Each individual stage necessitates numerous engineering efforts…
Sparsity-guided Network Design for Frame Interpolation
Tianyu Ding, Luming Liang, Zhihui Zhu +2
DNN-based frame interpolation, which generates intermediate frames from two consecutive frames, is often dependent on model architectures with a large number of features, preventin…
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
Jinxin Zhou, Xiao Li, Tianyu Ding +3
When training deep neural networks for classification tasks, an intriguing empirical phenomenon has been widely observed in the last-layer classifiers and features, where (i) the c…
Uplink Performance Analysis of Dense Cellular Networks with LoS and NLoS Transmissions
Tian Ding, Ming Ding, Guoqiang Mao +3
In this paper, we analyse the coverage probability and the area spectral efficiency (ASE) for the uplink (UL) of dense small cell networks (SCNs) considering a practical path loss…